The relevance and practical significance of the is caused by pervasive impact of container transportation on the economy of the Russian Federation, which is reflected in the State strategy for the development of the transport industry. Expansion of the network of multimodal transport and logistics hubs for handling container cargo should increase their capacity, ensure the growth of transit cargo and the inflow of private Russian and foreign investments in rail transport. The purpose of the research is to develop a forecast for the rail container transportation market in the Russian Federation and estimate its impact on GDPusing mathematical and statistical tools based on publicly available information base. The research methodology included the following stages: industry analysis, identification of trends and their assessment; development of a regression model for market forecasting, taking into account the identified factors and information available in the public domain; assessment of the impacts of factors on GDP; taking into account the development risks of the rail container transportation market. Industry analysis, a systematic approach and graphical methods were used to refine the methodology for forecasting the container transportation market by rail in the Russian Federation. The article shows that the key factors influencing the forecast of the development of the rail container transportation market are: advantages over other modes of transport in speed, quality, convenience and cost of cargo delivery; growth of containerization cargo base; transit prospects for developed and developing countries. Based on the data of Rosstat and PJSC Russian Railways, the regression model was built for the dependence of the volume of the Russian Federation’s GDP on the dynamics of the rail container transportation market, which allowed to predict the increase of GDP by 2025 compared to 2022 by 20.4% due to the growth of the rail container market, in in particular, due to imports by 55.2%, due to exports by 77.8%, and transit through the Russian Federation by 101.3%. The practical significance of the study is to assess of industry trends and risks in the short and medium-term implementation of the development strategy for the transport industry of the Russian Federation, which allows to substantiate the investment attractiveness of the industry.

Influenced by the governmental policy of national economy decarbonization and greening fundamentally new institution of green finance is currently developing in Russia. One of the key areas for the development of green finance is industrial waste disposal. The aim of the paper is to determine the efficiency of green financing of industrial waste utilization projects in Russia. The methodological basis of the paper consists of domestic and foreign scientific articles in the field of green financing and waste disposal, regulatory legal acts of the Russian Federation, as well as Rosstat data on the volume of industrial waste disposal. As a research method, the authors applied an analytical approach to systemize green finance concept definitions, and analyzed foreign experience of using green financial instruments in the industrial waste management industry. The article represents the content analysis of the Russian taxonomy of green and adaptation projects, as well as an assessment of the industrial waste utilization volumes that can potentially be achieved due to the implementation of projects within the framework of taxonomy areas. The results of the analysis show that through the implementation of green and adaptation projects, it is possible to additionally dispose of about 91 million tons of industrial waste, or 2.5% of the total volume of waste generated. Such a low recycling rate is a result of the limited amount of industrial waste types, the utilization of which is included in the taxonomy. It is necessary to expand the list of industrial waste, the disposal of which can be recognized as an independent project or a criterion for the implementation of projects within the framework of the taxonomy.

The relevance of the article is determined by solving the problems of expansion of BigTech-companies’ activities in the field of payments, which take place at present. The aim of the article to identify perspective directions of interaction of ecosystems with credit institutions in the payment sector. The authors used the following methods: system-functional, system-structural, statistical analysis and synthesis. The research analyzed current approaches to the definition of ecosystems and digital platforms and proposed the authorial interpretation; identified the main advantages associated with the participation of ecosystems in financial and payment intermediation; reviewed the models of provision of financial and payment services by ecosystems and identified the regulatory framework of their activities in foreign countries; proposed criteria for assigning a company to an ecosystem in Russia and marked out prospects of ecosystem activities in the payment sector. It is concluded that an ecosystem is a new institutional unit that has advantages in comparison with traditional financial institutions: the presence of a global customer base, the possibility of rapid implementation of network effects, the lack of excessive regulatory burden. Objective criteria that allow to assign a company to an ecosystem are: general and specific criteria that take into account the country characteristics of doing business, the level of development of the financial market, information technology, etc. Regulation of activities of ecosystems of the BigTech-companies allows to minimize basic, global and country risks by improving financial regulation and antimonopoly legislation, developing of unified standards and requirements for cross-border activities of ecosystems of BigTech-companies. The main scenarios of interaction between traditional financial institutions and ecosystems in the Russian financial and payment markets are: preservation of the dominance of traditional financial institutions; cooperation between banks and ecosystems; competition between banks and ecosystems; transition to a financial ecosystem dominance scenario.

The goal of the study – development of specific methodical reasoned proposals on improvement of the mechanism for ensuring sustainable development of the national banking system and its security against external challenges and threats to cyberspace. The scientific novelty consists in a comprehensive analysis of the processes of ensuring the cyber stability of the Russian banking system in the context of escalation of external challenges and threats to the digital economy. The authors used the following methods: general scientific (observation, comparison, measurement, analysis and synthesis, logical reasoning method), specific scientific (static analysis, peer review, graphical method). In the article conducted a critical review of domestic and foreign scientific literature and practical recommendations to ensure the protection of the banking institution from cyber threats in the digital economy; presented a comparative analysis of the organization of the cybersecurity system in the Russian and foreign banking systems; done multidimensional statistical analysis of cyber threats for Russian banks; substantiated recommendations and proposals on organizational, economic and legal improvement of the system of protection of Russian banks from internal and external cyber threats. As a result, it is shown that the main problem points (zones) of the banking system, creating the prerequisites for the occurrence of cyber-risks are: 1) there is no exchange of information on cyber-attacks and their mechanisms; 2) banks interact inefficiently with the state regulator of Internet – Roskomnadzor; 3) low level of competence of bank employees who are responsible for cybersecurity; 4) limited budget of small and medium-sized banks that wouldn’t allow them to care independent cyber-protection units; 5) growing popularity of new fintech services and new fintech companies. The author draws a conclusion that the following measures are necessary for organizational, economic and legal improvement of the system of protection of Russian banks from internal and external cyber threats: the processes of development of banking ecosystems should be intensified; a federal interbank register of cyber fraudsters must be created; a single banking «polygon» for testing cyber threats needs to be developed.

The transformation of the modern global monetary and financial system involves the elimination of institutional and functional contradictions existing at various levels. Some contradictions arose as a result of the asymmetric development of the global financial market (GFM). The aim of the article is to substantiate the asymmetry of the GFM development as an organic phenomenon, which, on the one hand, becomes a serious obstacle to the functioning and progressive development of the world economy, and, on the other hand, is the driving force behind this development. The authors apply general logical, theoretical, empirical, and special research methods. The origins of the asymmetric development of the GFM are determined. Endogenous and exogenous factors of GFM asymmetry were revealed. The article considers examples of asymmetry in various GFM segments. The negative impact of the global financial and economic crisis of 2008–2009 and the coronavirus pandemic on increasing the asymmetry of the GFM development has been determined. Based on the analysis of the key macroeconomic indicators of the top 20 countries in terms of GDP, the asymmetric nature and the absence of stable patterns that determine the country’s position in the world ranking are revealed. The authors conclude that the asymmetry of the GFM development is an organic phenomenon, caused by a wide range of causes of endogenous and exogenous nature. Endogenous asymmetries can be partially compensated either through complete economic isolation, which is likely to lead to a slowdown in development and lagging behind other countries in the future or through active involvement in a system of world economic relations based on fair partnerships. Exogenous asymmetry, due to the peculiarities of the historically established world order, is destructive for all participants in the global economic system, including those whose interests must be protected in the first place.

The article defines and analyzes the features, factors, and directions of transformation of the model of regional monetary and financial integration of the countries of the Eurasian Economic Union (EAEU). The aim of the study is to develop and systematize a set of measures to develop the investment direction of integration cooperation between the EAEU countries, reduce their dependence on the highly volatile international economic and financial environment and neutralize the negative impacts of Western sanctions for national economies. The objectives of the study are as follows: analysis of trends and problems of the investment process in the economies of the EAEU countries for 2013–2021, substantiation of proposals and recommendations for optimizing the model of integration financial and economic cooperation of the EAEU countries based on increasing the regulatory role of the state and regional financial institutions in attracting investments. The research methodology includes the analysis of the EAEU legal framework, statistical information, official reports of state bodies of the EAEU countries and the Eurasian Economic Commission, regional development institutions, scientific monographs and publications of Russian and foreign economists, and periodicals. Based on the methods of econometric analysis, the expediency of introducing into circulation a monetary unit of collective use of the EAEU countries independent of the US dollar and euro for mutual settlements is substantiated. The authors conclude that it is necessary to supplement and, in some cases, substitute the predominantly market-oriented model of Eurasian financial and economic integration with a regulatory investment model of regionalization with an increased role of national and regional management institutions in promoting integration processes.

The research aims to examine the unexpected changes in stock prices due to external shocks given to the macroeconomic variables to forecast future stock market returns. The study applies two econometric models such as «Variance Decomposition» (VDC) and «Impulse Response Function» (IRF) for examining the exogenous shocks in macroeconomic variables respond to changes in stock prices. Monthly time series data of five significant macroeconomic variables Real Exchange Rate, Interest Rate, Consumer Price Index (CPI), Crude Oil Prices, and Trade Openness, taken as independent variables and BSE SENSEX as a dependent variable. The research period is from Jan 2009 to Dec 2019. The study has taken the responsibility to reveal a few strong evidences for changes in stock prices due to exogenous shocks in Exchange Rate, Trade Openness, Inflation, and Interest rate along with crude oil prices. According to the results, changes in the stock market are due to external factors like changes in dividend policy or capital loss, and some changes in the stock market are due to its own innovative shocks. This study suggests to reduce unexpected changes in stock prices frequently, companies should control capital loss and focus on stable return/dividend policies. There are divergent views in the literature review in the context of measures of these variables, however no research has been done on exogenous shocks in macroeconomic variables to BSE SENSEX for the Indian stock market with this particular data set and duration.

The subject of the research is the influence of the debt burden of state-owned companies on the dynamics of Russia’s corporate external debt. The relevance is due to the unprecedented combination of sanctions in 2022, which created default risks of national companies. The goal of the article is to identify factors influencing changes in the amount of external debt. Based on a quarterly sample for 2010–2019 (37 observations), using the least squares method (LSM), a regression model was built for the dependence of corporate debt dynamics on micro– and macroeconomic factors (debt service ratio and credit rating of companies, foreign assets, ACRA financial stress index, rate changes of USD/RUB, credit default swap (CDS), export volume, balance of payments). An analysis of their credit risk was carried out by comparing the dynamics of the debt sustainability ratio (DSR) with the rating and cost of CDS, and the quarterly income support of debt was calculated. As a result of testing the hypotheses, a positive relationship was revealed between DSR and ratings of state-owned companies for changes in banks’ external debt, while for enterprises they do not play a key role. It was concluded that the growth of loan premiums in 2014–2015 was due to political factors, and by the new crisis, the companies had accumulated reserves for absorbing the shock. Measures are proposed to reduce debt risks – coordination of debt policy, debt «import substitution», monitoring of new financial indicators of companies, control of cross-border capital flow, etc.

The bankruptcy of Russian companies in the existing environment has become rather common. Determination of bankruptcy risk factors allows predicting the prospects for business development. The authors set the task to determine the relative influence

of individual financial and non-financial factors on the probability of a company’s bankruptcy. To study risk factors, the authors analyzed 3184 large Russian companies (with revenues of more than 2 billion rubles per year and more than 250 employees) of various industries operating from 2009 to 2020. The total number of observations is 38,208. For analysis, 30 factors were selected and divided into five groups: profitability, liquidity, turnover, financial stability and general (non-financial) factors. For the study, one of the machine learning methods was used – the random forest method. The sample consists of companies from seven industries, including manufacturing, retail, construction, electric power, mining, agricultural production, and water supply, as well as other industries, which include companies in education, healthcare, agriculture, and hospitality. The analysis was carried out both in aggregate for the entire sample without being distributed by industry, and for samples distributed by manufacturing, retail, and service industries. In the sample as a whole, the tested model in 86% of cases correctly predicted the possibility of a company going bankrupt for the period under review. This result confirmed that machine learning methods (in particular, the random forest algorithm) are highly effective in solving the problem of bankruptcy prediction for a company. Based on the data obtained, the paper concludes that profitability factors have the most significant impact on the probability of bankruptcy for manufacturing and retail companies. For service companies, it is financial stability factors. Solving the problem of determining the bankruptcy risk factors of Russian companies will ensure a reduction in the number of bankrupt enterprises, which, in turn, will contribute to the recovery and development of the national economy.

The implementation of financial and analytical procedures is an important stage of making appropriate management decisions in the implementation of economic activities. During the financial analysis of the organization’s activities can determine such indicators as the level of financial stability, solvency, liquidity of the company, its market value and other important indicators, without knowledge of which it is difficult to make adequate and effective management decisions. The purpose of the study is to determine the financial instruments of equating certain categories of an organization’s liabilities to its own funds within the framework of financial and analytical procedures. During the research, the author used such methods as content analysis of sources, analysis, synthesis, generalization, scientific abstraction, analogy. The author shows that the interpretation of the concept of «obligation» from the point of view of various areas of economic science (accounting, audit, taxation, valuation, financial analysis, etc.) can have different meanings. The author analyzed a number of normative legal acts and the practice of applying retraining (equating) obligations to own funds. As a possibility of equating obligations, the author considers subordinated borrowed funds; long-term borrowed funds and long-term accounts payable; minimum regulatory accounts payable arising as a result of a gap in the terms of accrual and payment (fixed liabilities); debt and accounts payable to affiliated entities; certain elements of deferred income; certain elements of reserves future expenses and other equated to own funds of obligations. It is concluded that individual liabilities, considered by accounting science and jurisprudence as liabilities, from a financial point of view (in certain situations, taking into account the relevant goals and objectives of financial analytical procedures), can be equated to the organization’s own funds.

The aim of the present study is to present the results of the approbation of the methodology of the averaged method of chain substitutions for three and four-multiple and multiplicative-multiple factor models and to systematize in tabular form all mathematical expressions developed so far to determine the individual factor influences by types of factor models. The relevance of the research is caused by the disadvantages and the limited applicability of the methods of deterministic factor analysis developed so far, which is one of the areas of financial and economic analysis. The scientific novelty of the research is the new mathematical expressions developed by the author for determining the individual factor influences according to the methodology of the averaged method of chain substitutions for three and four multiple and multiplicative-multiple factor models. Previous and new mathematical expressions according to the averaged method of chain substitutions are systematized by types of factor models in tabular form. The main conclusion is that the averaged method of chain substitutions has complete universality of application for all types of factor models and is characterized by accuracy and unambiguity of the results obtained for quantification of individual factor influences.

The purpose of this study is to examine the managerial impacts of applying modern public financial management (MPFM) tools in financial reform programs on the efficiency of public financial management (PFM) in developing countries, considering the case of the Egyptian reform program implemented during 2005–2015. Applying MPFM tools could improve the efficiency of PFM in developing countries if institutional factors are available to ensure their successful implementation in reform programs. The study adopted a descriptive-analytical method to describe the managerial impact of applying MPFM tools in the financial reform experiences in developing countries. It employed a case study approach on the Egyptian reform experiment to estimate the correlation between applying modern financial tools and the managerial efficiency of PFM assessed through three elements: operational efficiency, allocative efficiency, and financial discipline. The practical study used the IBM SPSS package and MS-Excel to process the data. The results found a positive correlation between the application of modern financial tools and the rate of improvement in the efficiency of PFM in the Egyptian reform program. The study developed a specific model for a deeper understanding of the impacts of MPFM tools on the efficiency of PFM. The model highlighted a strong positive correlation between the successful application of modern PFM tools and the efficiency of PFM and underscored that the availability of the required realtime financial information about governmental revenue and more control over public spending led to achieving financial discipline.

Micro, small, and medium enterprises (MSME) are the backbone of every economy. Financial inclusion of MSMEs is essential for any country aspiring to economic development. Innovative solutions offered by fintech companies can support the financial inclusion of MSMEs. Digital payments, alternative loans, insurance, investments, regulatory, and robo-advisory services are just a few of the services that fintech companies provide to MSMEs. The purpose of this studyis to examine the role of financial technology on registered micro, small, and medium enterprises in India. The objective of the study is to reveal the behaviour of MSMEs towards financial technology acceptance and show how various demographic variables of owners/managers influence the acceptance of financial technology in the case of MSMEs. The methodological basis of the study is a management survey of 117 MSMEs in India. The questionnaire had 25 questions; measurement items used in the questionnaire were derived from previous studies carried out in developing countries. The results were processed and tested for significance using modern econometric methods such as the Kruskal-Wallis H test, and the Mann-Whitney U test. The result of the study indicates that the financial technology acceptance rate among the MSME sector is high as maximum MSMEs consider themselves moderate financial technology adopters. MSMEs have a high understanding of different financial services provided by fintech companies. Prior Experience of the owner/manager, brand familiarity, government support, and behavioural variables such as perceived ease of use, perceived usefulness, trust, and satisfaction was proved to be effective while adopting financial technology services whereas, demographic variables such as gender, age, education level of owner/manager was found to be ineffective. The study concludes that fintech companies are providing quality services by acting as a single window, supporting the financial needs of MSMEs at low interest rates, simplified processes and lower transaction costs. MSMEs are using fintech products and services as a key part of their financial management, with increasing adoption there is a growing opportunity for fintech companies, incumbents, and non-financial organisations. The result of the study contributes to the novel understanding of the acceptance and preference of the MSME sector towards financial technology.

The article is devoted to the research of the issues of commercial bank business valuation under the conditions of uncertainty. The study aims to develop a model for forecasting the value of total assets and loan portfolio of a commercial bank within the framework of value estimation under external uncertainty. The relevance of the paper is that in the context of the COVID‑19 pandemic, military actions and sanctions pressure it is difficult to justify the market value of credit institutions due to the difficulties in implementing the methodology of assessment of banks whose business is associated with increased risks. The scientific novelty of the study lies in the development of a regression model that allows forecasting the value of total assets and the loan portfolio of a commercial bank as key value factors under external uncertainty. The authors used the following methods of scientific research: deduction, induction, correlation and regression analysis, and logical method. The key factors of business valuation of Russian banks are systematized. The authors propose to build a model within the framework of the income approach, based on the forecast of external cost factors: total assets and loan portfolio of the banking sector. A leading indicator that affects total assets and loan portfolio is justified. A model has been developed which makes it possible to forecast the total assets and loan portfolios of the banking sector and find the required value of the assets of the bank being evaluated through the market share. The model is tested on the example of the valuation of Sber. The authors conclude that the model developed by the authors makes it possible to build scenarios for future cash flows and quantify the valuation interval of a commercial bank. The prospect of further research is related to evaluating the influence of internal financial and non-financial factors in the context of the valuation management system. The article will be useful to practicing appraisers in business valuation and investors.

Increased spatial heterogeneity in recent years in the processes of attracting banking capital to the Russian economy negatively affects the pace of socio-economic development of regions. The purpose of the research is to assess the dynamics of changes in spatial heterogeneity in the processes of attracting banking capital in the Russian economy and to model the system of interregional relationships in these processes. Scientific novelty of research is the development of a methodological approach involving the systematic use of methods such as: spatial autocorrelation analysis according to the methodology of P. Moran and L. Anselin, regression analysis using panel data, testing cause-and- effect relationships using the Granger method, formation of a matrix of functional dependencies between regional systems. The developed methodological approach allowed to confirm the trend of increasing spatial heterogeneity in the processes of attraction of banking capital in the Russian economy, to identify regional centers with a high level of concentration and formation a matrix of interregional relationships. It is shown that almost all Russian banking capital is now concentrated in Moscow, St. Petersburg and the Kostroma region. The inflow of bank capital into the economy of these regions leads to its outflow from regions with inverse relationships (negative index of spatial autocorrelation). The results of the research can be used by the executive authorities of the federal and regional levels to find mechanisms to attract banking capital in the economy of regions. One such mechanism could be a reduction in the key rate of the Bank of Russia and State support for regional banks that use low interest rates for lending to households and enterprises in the real sector of the economy.

The article considers the results of the implementation of the pension reform in Russia in 2018, reflected in changes in labor market indicators according to Rosstat. The purpose of the study is to develop a scientific understanding of the processes of formation of the pre-pensioner segment of the Russian labor market under the influence of its external and internal factors. The authors use methods of statistical, correlation, and regression analyses, the calculation of the average for a certain integral of functions, as well as the method of linear modeling of multiple regression. The study assesses the scientific elaboration of the research topic abroad and in Russia. The issues of financial literacy of the population are analyzed. The financing of the training of pre-retirees in the professional competencies that are currently in demand on the labor market and support for unemployed pre-retirees who are registered with the employment center are considered. The selection of relevant demographic data and a sample labor force survey by age group has been carried out. The total number of pre-pensioners in 2018–2020 has been calculated and their structure according to the status of labor activity in the Russian labor market has been identified. The general dynamic, structural, and gender characteristics of the economic activity of pre-pensioners in the labor market are analyzed. The demand for pre-retirees by type of economic activity in 2019 is assessed. The authors conclude that there is a tendency to reduce the share of the pre-pensioner segment in the labor market after reaching the project retirement age threshold from 10.88% to 9.76%. The employment rate in this group of the population will be 66%. The study has established that the demand for pre-pensioners by type of economic activity in the labor market is 1.13 times higher for women than for men. A methodical approach has been developed to analyze the results of assessing the demand for state support measures by pre-pensioners. The article analyzes the influence of financial and social measures of state support for pre-pensioners on increasing their labor activity and competitiveness in the labor market. The results of the study can be used by the authorities to substantiate the assessment of the effectiveness of financing the measures they take to provide social and economic support to pre-retirees.

The goal of the study is to estimate the parameters of the stochastic wage process using data from the Russian Longitudinal Monitoring Survey of Higher School of Economics (RLMS-HSE). The main method of analysis is econometric estimation, which includes two steps. In the first step, the authors estimated a Mincer-type regression. In the second step, they estimated the parameters of the stochastic wage process using the generalized method of moments. As a result, the autoregression coefficient turned out to be lower, and the variance of shocks was higher than in similar foreign studies. The results of the research allow to conclude that labor incomes in Russia are less stable over time and are marked by great uncertainty. The practical value of the work lies in the possibility of using the obtained estimates when calibrating general equilibrium models with heterogeneous agents, which is demonstrated in the framework of estimation of macroeconomic effects from hypothetical tax maneuvers based on the canonical model with heterogeneous agents.

In the challenging and volatile financial markets, an investor needs to change his financial objectives frequently, leading to a diversified portfolio of investments. The financial future of the individual investor depends on his rational decisionmaking. This research aims to evaluate various determinants of financial decision-making concerning working women in the National Capital Region, India. It examines the association of financial literacy, personal finance planning, and risk

behaviour with the financial decision-making of working females. The research also studies the different exogenous variables of financial literacy, including financial attitude (FA), financial behaviour (FB) and financial knowledge (FK). It utilises a quantitative approach for predicting relationships between the identified variables. The study is based on primary data collected through a structured questionnaire designed on a 5-point Likert scale and was analysed through a partial least square-structural equation modelling (PLS-SEM) approach. The study results suggest a positive and significant association of financial literacy and personal finance planning with financial decision-making by working women. On the other hand, risk behaviour negatively affects financial decision-making. The findings also reveal that all three exogenous variables, financial attitude, financial behaviour and financial knowledge, have a strong relationship with financial literacy. The research is relevant for individual women investing in various financial avenues to take better decisions. This study also benefits financial managers and institutions to target as women are potential investors in a developing country like India.